Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision making. Data analysis may have multiple facets and approaches, encompassing diverse techniques. However, interpreting and analyzing different types of data may be very challenging, especially for users who are not very familiar with the data they are visualizing. One tool for helping users understand their data may be the use of a relevant visualization, such as a chart, of the data. Therefore, choosing a proper chart may greatly enhance a user's understanding and interpretation of their data.
In recent years, new types of charting engines have been developed that provide vast libraries of charts for industry specific data. The charting engines may prove to be a powerful new tool for data analysts. Some of the charting engines may allow new chart types to be created by a visualization author using a specification language. The specifications may then be applied to a given set of data in order to render a chart. Current charting engine technology includes charting engines, such as the Rapidly Adaptive Visualization Engine (RAVE). RAVE uses a specification adapted from the Grammar of Graphics definition. Although very powerful, such systems may still require a visualization author that is skilled in the language of the specification they need to create. These languages may often be very complex since they provide a rich set of chart features. Therefore, a typical user, who may simply want to understand their data may have to rely on the existing charts within the system that have been created by such experts.